[人工智能]opencv黑白线循迹

import cv2 as cv
import numpy as np
import time







def xunji():

    cap = cv.VideoCapture(0, cv.CAP_DSHOW)
    cap.set(3, 600)
    cap.set(4, 600)
    if cap.isOpened():
        while 1:
            ret, frame = cap.read()
            res = cv.resize(frame, None, fx=0.5, fy=0.5)
            cv.imshow("res", res)

            #   颜色空间转换
            res1 = cv.cvtColor(res, cv.COLOR_BGR2GRAY)
            res2 = cv.cvtColor(res, cv.COLOR_BGR2HSV)

            #   图像阈值设置
            ret0, thresh1 = cv.threshold(res1, 80, 255, cv.THRESH_BINARY)

            #   高斯滤波
            blur = cv.medianBlur(thresh1, 5)

            #   形态学运算
            kernel = np.ones((5, 5), np.uint8)
            cvOpen = cv.morphologyEx(blur, cv.MORPH_OPEN, kernel)  # 开运算
            cv.imshow("cvOpen", cvOpen)

            #   kirsch算子
            m1 = np.array([[5, 5, 5], [-3, 0, -3], [-3, -3, -3]])
            m2 = np.array([[-3, 5, 5], [-3, 0, 5], [-3, -3, -3]])
            m3 = np.array([[-3, -3, 5], [-3, 0, 5], [-3, -3, 5]])
            m4 = np.array([[-3, -3, -3], [-3, 0, 5], [-3, 5, 5]])
            m5 = np.array([[-3, -3, -3], [-3, 0, -3], [5, 5, 5]])
            m6 = np.array([[-3, -3, -3], [5, 0, -3], [5, 5, -3]])
            m7 = np.array([[5, -3, -3], [5, 0, -3], [5, -3, -3]])
            m8 = np.array([[5, 5, -3], [5, 0, -3], [-3, -3, -3]])

            filterlist = [m1, m2, m3, m4, m5, m6, m7, m8]  # 将各个方向的卷积核放到一起便于统一操作
            filtered_list = np.zeros((8, cvOpen.shape[0], cvOpen.shape[1]))  # 建立三维数组，第0维表示各个方向卷积后的值

            for k in range(8):
                out = cv.filter2D(cvOpen, cv.CV_16S, filterlist[k])  # 自定义卷积，其实里面的步骤跟Sobel算子是差不多的
                filtered_list[k] = out

            final = np.max(filtered_list, axis=0)  # 取八个方向中的最大值，也就是取第0维的最大值作为图像该点，滤波之后的新的像素值
            final[np.where(final >= 255)] = 255  # 令像素值大于255的点等于255
            final[np.where(final < 255)] = 0  # 令像素值小于255的点等于0
            cv.imshow("final", final)



    #   判断
            try:
                m = []
                w = []
                p = []
                height = int(final.shape[0])
                width = int(final.shape[1])
                i = 0
                while i < height-1:
                    n = []
                    if len(m) < 20:

                        for j in range(10, width-1):

                            if final[i, j] == final[i, j+1] and final[i, j+1] == 0:
                                j += 2
                            elif final[i, j] != final[i, j+1] and final[i, j + 1] == 255:
                                n.append(j+1)
                                # print(n)
                    if len(n) != 0:
                        w.append(n)
                        m.append(len(n))
                    i += 2

                a = 0
                t = 1
                for k in range(len(m)):
                    if m[k] == 0:
                        p.append(0)
                    if m[k] == 1:
                        p.append((2*w[k][0] + 40)/2)
                    if m[k] == 2:
                        p.append((w[k][0] + w[k][1])/2)
                    if m[k] == 3:
                        p.append((w[k][0] + 40)/2)
                # if 60 < sum(m) <= 80 and a == 0:
                #     if t == 1:
                #         p.append((w[k][0] + w[k][1]) / 2)
                #     elif t == 2:
                #         p.append((w[k][3] + w[k][2]) / 2)
                #     elif t == 3:
                #         p.append((w[k][0] + w[k][1]) / 2)
                #     elif t == 4:
                #         p.append((w[k][0] + w[k][1]) / 2)
                #     a = 1
                # elif m[k] == 2 and a:
                #     t += 1
                #     a = 0


                p.remove(max(p))
                p.remove(min(p))
                print("距离中心：%.2f" %(165-sum(p)/(len(p)-1)))
            except Exception as e:
                print(e)
            low_yellow = np.array([26, 43, 46])
            high_yellow = np.array([34, 255, 255])
            mask = cv.inRange(res2, low_yellow, high_yellow)
            open = cv.morphologyEx(mask, cv.MORPH_OPEN, kernel)
            edges = cv.Canny(open, 10, 20)
            cnts, _ = cv.findContours(
                edges, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
            if len(cnts) > 0:
                break
            cv.imshow("mask", edges)

            if cv.waitKey(1) == ord('q'):
                break
    cap.release()
    cv.destroyAllWindows()


if __name__ == "__main__":
    xunji()